Residential and commercial sectors - IMACLIM
|Model Documentation - IMACLIM|
|Institution||Centre international de recherche sur l'environnement et le développement (CIRED), France, http://www.centre-cired.fr., Societe de Mathematiques Appliquees et de Sciences Humaines (SMASH), France, http://www.smash.fr.|
|Solution concept||General equilibrium (closed economy)|
|Solution method||SimulationImaclim-R is implemented in Scilab, and uses the fonction fsolve from a shared C++ library to solve the static equilibrium system of non-linear equations.|
|Anticipation||Recursive dynamics: each year the equilibrium is solved (system of non-linear equations), in between two years parameters to the equilibrium evolve according to specified functions.|
In the structure of the IMACLIM-R model, the use of energy in the residential sector is determined in each static equilibrium via the αm2 parameters. The parameters acts as a physical constraint on household budgets because they are directly linked to the physical stock of buildings available during the current period, and to the coefficients of unit consumption of energy (kWh/m2) rather than to the maximization of utility. Determining residential sector energy use in the static equilibrium thus means assuming that its energy demand for various end-uses is inelastic to price and income variations over the short term. Hence, households' energy demand depends mainly on the equipment choices they have made over the preceeding years.
In the dynamic modules, the amount of living space per capita changes according to the income per capita which isdetermined endogenously in the preceding static equilibrium. It is assumed that there is an asymptote of floor area per capita specific to each region, and that the asymptote incorporates spatial constraints, choices in the styles of building development and density and cultural habits. In the construction of scenarios, the assumptions made about these asymptotes are kept consistent with those concerning the development of transport infrastructure, bearing in mind that all such dynamics are linked to territorial and urban zoning policies.
The equation below relates the evolution of floor area per capita for the residential sector to the evolution of income per capita, Income_pck, over the two preceding static equilibrium periods and an elasticity,αk(m2_pc(t)), which decreases as floor area per capita increases:
The total residential floor area, Sk;housing, is the product of this surface per capita and of the total population. The newly constructed residential surface is equal to the difference between this total surface and the old residential surface depreciated by the surfaces at end of life (lifetime, Life_timek;housing):
Energy use per m2 depends on the average composition of equipment installed in the housing stock, and of the thermal charachteristics of building construction. Their evolution depends on the choices agents' technological make in responce to different economic signals and the available technologies.
In the reference scenario, energy use per m2,αm2k;ener (t + 1), evolves according to an exogenous trajectory calibrated to outputs from the POLES energy model, that have themselves been calculated to be coherent with macroeconomic trajectories from IMACLIM-R during coupling exercises between the two models. This trajectory encompasses the evolution dynamics of household equipment, the conversion efficiency betweenbetween final energy and energy services and the buildings physical characteristics (insulation, use of renewable energies).
In the emission reduction scenarios the carbon price signal induces efficiency gains in building phyisical charachteristics and equipment. These technological options are represented with a unique type of alternative housing called a Very Low Energy building (VLE) whoose annual energy consumption is 50kWh/m2 (80% electricity and 20% gas). Technologies which can bring about this level of unit energy consumption are already commercialised e.g. on-site energy production of energy and efficient insulation of buildings, and are represented in the model in an aggregated manner. To increse the deployment of VLE?s we assume the introduction of what we call technological rupture policies, expected to launch large scale thermal renovation plans and the tightening of building regulations in the developing countries. Following this scheme, two types of housing can coexist in the same stock: (i) standard homes (BAU) which have the same energy characteristics as those of the reference scenario and incorporate progressive gains in energy efficiency and (ii) newly built Very Low Energy (VLE) homes. The penetration speed of VLE's into the building stock is determined by two reduced functional forms that link the level of a carbon tax to (i) the percentage of new built dwellings that are VLE's and (ii), the annual rate of renovation in the existing building stock that converts a BAU into a VLE (with a maximum annual rate fixed at 2,5%). This maximum level is reached at a carbon price of $100 per ton of CO2 while VLE buildings begin to penetrate the market from $10 per ton of CO2.
Unit consumption of the existing dwelling stock is then obtained by averaging the energy characteristics of the BAU and VLE housing stocks, weighted by their shares in the total dwelling stock.
The evolution of this composite sectors (aggregating light industries and services) intermediate consumption of energy follows the same structure of representation as that of the industrial sector (see following section).